Personality traits as predictors of the social english language learning strategies

INTERNATIONAL JOURNAL OF BEHAVIORAL SOCIAL AND MOVEMENT SCIENCES Vol.01,July2012,Issue03

PERSONALITY TRAITS AS PREDICTORS OF THE SOCIAL ENGLISH

LANGUAGE LEARNING STRATEGIES

Seyed Hossein Fazeli

Shoushtar Branch, Islamic Azad University, Shoushtar, Iran
fazeli78@yahoo.com
______________________________________________________________________________

ABSTRACT

The present study aims to find out the role of personality traits in the prediction use of the
Social English Language Learning Strategies (SELLSs) for learners of English as a foreign
language. Four instruments were used, which were Adapted Inventory for Social English
Language Learning Strategies based on Social category of Strategy Inventory for Language
Learning (SILL) of Rebecca L. Oxfords, A Background Questionnaire, NEO-Five Factors
Inventory (NEO-FFI), and Test of English as a Foreign Language (TOEFL). Two hundred and
thirteen Iranian female university level learners of English language as a university major in
Iran, were volunteer to participate in this research work. The intact classes were chosen. The
results show that however, there is a significant relationship between four traits of personality
and use of the SELLSs, but personality traits cannot be as a strong predictor to predict use of the
SELLSs.
Key Words: Social Language Learning Strategies, English Learning, Personality Traits, English
Learners
_________________________________________________________________________

INTRODUCTION:
Since individual differences have been identified as variables influencing language learning
outcome (Larsen-Freeman & Long, 1991; Skehan, 1989); and as it was shown by the study of
Marttinen (2008), the high percent of source of learners’ knowledge comes from teacher;
Horwitz (1988) encourages teachers to discover the prescriptive belief of their own students.
Moreover, in order to provide successful instruction, teachers need to learn to identify their
students’ individual difference, and even they need to become more aware that how their
teaching styles are appropriate to their learners’ strategies (Oxford & Cohen, 1992).
Recently some studies tend to concentrate more on individual differences in strategy
performance (e.g. Oxford, 1992, 1993; Toyoda, 1998). In such related studies, it was showed that
for strategy instruction to be affected; it should take all the variables into account (Oxford &
Crookball, 1989).
Since 1990s, there has been a growing interest on how personality correlates to the academic
performance. Personality has been conceptualized at different levels of breadth (McAdams,

On-Line International Blind Peer Reviewed Indexed Journal 9


1992), and each of these levels include our understanding of individual understanding.
Moreover, individuals are characterized by a unique pattern of traits, and some study shows
successful language learners choose strategies suit to their personalities (Oxford & Nyikos,
1989). In addition, since LLSs are not innate but learnable (Oxford, 1994), broad justifications
have been offered for the evaluation of personality traits as a predictor of the Social English
Language Learning Strategies (SELLSs).
In such way, the premise underlying line of this research is that success in SELLSs plays an
important role in affecting learners’ English language learning process.
REVIEW OF THE LITERATURE:
The studies on individual and personality differences are a central theme in psychology as well
as the other areas of social and behavior sciences (Saklofske & Eysneck, 1998).
The examination of variation in human behavior is referred to as the study of individual
differences (Ehrman & Dornyei, 1998). Such study of individual differences includes many
subsets of studies such as the study of personality differences (Hampson & Colman, 1995), and
personality factors that are important in development of linguistic abilities (Ellis, 1985).
Psychologically, it is a truism that people are different in many fundamental ways, and learners
are individuals, and there are infinitive variables (Skehan, 1989). In this manner, Horwitz (1999)
points out “language learners are individuals approaching language learning in their own unique
way” (p.558). In addition, individuals who are characterized as a particular psychological type,
adopt different learning strategies (Brown, 2001).In such situation, the teachers must make the
students aware of the range of the strategies they can adopt (Cook, 2008); and they must aware
of the relationship between personality and academic performance (Cattel & Butcher, 1968;
Eysenck, 1967).
Foregoing has highlighted the main goal of the current study to document how personality traits
related to the SELLSs. In such situation, there are some possible ways looking at the SELLSs
and their relationship with personality traits. The first is to see the use of the SELLSs as an
outcome of personality traits. The second one is to see them as having uni-directional causal role
increasing personality traits. The third one is to see the relationship between the two as mutual,
and causality is bi-directional.
METHODOLOGY:
Participants-
The participants for this study were 213 female studying in third grade (year) of English major
of B. A. degree, ranging age from 19 to 28 (Mean = 23.4, SD = 2) at Islamic Azad University
Branches of three cities which named Abadan, Dezful ,and Masjed-Solyman, Iran, were asked to
participate.
The socio-economic status of participants, such as the participants’ social background, and
parents’ level education was controlled as well by a questionnaire. Based on some indicators
such as the parents’ socio-educational background and occupation, the participants were matched


as closely as possible for socio-economic background to minimize the effect of social class.
Accordingly, the participants were classified as a middle class.
Because of the nature of this work (regarding use of the SELLSs), a general English proficiency
test for determining the proficiency level of participants in English was applied in order to
minimize the effect of English language proficiency. As Jafarpour (2001) defines “the percent
classification of subjects by the experimental test that corresponds to those by the criterion”
(pp.32-33) (as cited in Golkar & Yamini, 2007), top of subjects are 27% and bottom of subjects
are 27% (Golkar & Yamini, 2007), the participant whom were classified as intermediate
subjects, were asked to participate in the study.

INSTRUMENTATION IN THE STUDY:
Four instruments were used to gather data in the current study.
Adapted Inventory for Social English Language Learning Strategies -
The Strategy Inventory for Language Learning (SILL) of Rebecca L. Oxford (1990) is a kind of
self-report questionnaire that has been used extensively by researchers in many countries, and its
reliability has been checked in multiple ways, and has been reported as high validity, reliability
and utility (Oxford, 1996). In addition, factor analysis of SILL is confirmed by many studies
(Hsiao & Oxford, 2002; Oxford, 1996; Oxford & Burry-Stock, 1995).In this way, as Ellis (1994)
believes Oxford’s taxonomy is possibly the most comprehensive currently available. Several
empirical studies have been found moderate intercorrelation between the items of six categories
in SILL (Oxford & Ehrman, 1995).
The SILL includes Memory Strategies (9 items), Cognitive Strategies (14 items), Compensation
Strategies (6 items), Metacognitive Strategies (9 items), Affective Strategies (6 items), and
Social Strategies (6 items).
Based on the Social category of the SILL, the investigator adapted a questionnaire. In
adaptation of each instrument from one language to another in research works, some problems
occur, such as the problem of translation one questionnaire to another language (Perera &
Eysenck, 1984). As same as the other two questioners (NEO-FFI and Background
Questionnaire), adapted SELLSs inventory was checked through back translation into English by
three English teachers, and three psychologists who were fully proficient in both languages
(English and Persian), in order to check the consistency with English version, and based on the
pilot study was performed. The items were corrected until full agreement among the translators
was achieved, and the pilot study confirms such translated items. In addition, the balance
between spoken and written Persian was checked.
In the case of such questionnaire, three psychologists, and three English teachers were asked to
check the questionnaire from two points of view. Firstly, since both psychologists and linguists
were fully proficient in both languages (English and Persian), they were asked to check the
translated version of the questionnaire in order to check the consistency with English version of



them. Secondly, since both the psychologists and English teachers were professional in related
study of the questionnaire, they were asked to check the psychometrics of the questionnaire.
After full agreement among the psychologists and linguists was achieved, and the pilot study
confirmed the items of such questionnaire, it was administrated in the main study.
Test of English as a Foreign Language (TOEFL)
A Background Questionnaire
NEO-Five Factors Inventory (NEO-FFI)
The Big Five Personality Questionnaire is based on the Big Five Factor Model of personality
whose major proponents are Lewis Goldberg, Paul Costa, and Robert McCare. This theory
proposes that five broad dimensions provide complete description of personality.
The questionnaire of the Big Five Factors is one of the most widely used personality assessment
in the world. In addition, evidences indicate that Big Five is fairly stable over time (Costa &
McCare, 1988; Digman, 1989). Moreover, factor structure resembling the Big Five Factors was
identified in numerous sets of variables (Digman & Inouye, 1986; Goldberg, 1981, 1990; John,
1990; McCare & Costa, 1985; Saucier & Goldberg, 1996). In addition, the scales of Big Five
personality have proven to be a useful tool in a number of applied fields. In this way, the Big
Five Factors Inventory has enjoyed wide spread popularity in applied organizational context. The
reliability reported in the manual is adequate with mean of .78 across the five factors (Costa &
McCare, 1992).
The idea of major dimensions include much of personality is long standing (Norman, 1963). In
addition, Digman and Inouye (1986) state “the domain of personality of personality descriptors is
almost completely accounted for by five robust factors” (p.116). In this way, the Big Five
Factors personality questionnaire can be as a satisfactory tool to assess the relationship between
personality and a number of academic variables (Chamorro-Premuzie, Furnham & Lewis, 2007).
Despite the FFI enjoys international use, but the Big Five structure has not been accepted
generally (Block, 1995; Eysenck, 1992, 1997; McAdams, 1992).
The dimensions composing the Big Five Factors (as cited in related literature by different
dominant researchers such as Chamorro-Premuzie, Furnham & Lewis, 2007; Costa & McCare,
1992) are detailed as: a) Neuroticism represents the tendency to exhibit poor emotional
adjustment, anxious, and pessimistic; b) Extraversion represents the tendency to be sociable and
assertive, cheerful, active, upbeat, and optimistic; c) Openness to experiences (intellect)
represents the tendency to imaginative, intellectually curious, imaginative, and artistically
sensitive; d) Agreeableness is the tendency to be trusting, compliant, caring, gentle,
compassionate, empathic, and cooperative; e) Conscientiousness represents the tendency to
responsible, organized, hard-working, responsible, dependable, able to plan, organized,
persistent, achievement oriented, purposeful, strong-willed, and determined.
The NEO-FFI is a sixty-item version of S form of the NEO-PI-R that is applied to measure the
five domains of personality. It is consist of five 12-item scales. Each of these sixty items includes


five options. As same as the adaptation of the SILL, the participants were asked to choose the
statement which how true of them it is. They were told that answer must be in terms of how well
the statement describes them. In addition, they were told that there is no right or wrong answer to
these statements. The NEO-FFI is self-scoring, and paper and pencil survey. The options were
as: a) Strongly Disagree, b) Disagree, c) Neutral, d) Agree, e) Strongly Agree.
SAMPLE OF THE PILOT STUDY:
The sample for the pilot study, as “A small-scale replica and a rehearsal of the main
study” (Riazi, 1999, p.198), was selected so as it represents the entire sample for participants
whom asked to participate in the main study. Since sample size in pilot study ranges from 20 to
bigger of 65 (Hinkin, 1998), thirty nine female students were asked to participate in the pilot
study.
RELIABILITY OF THE INSTRUMENTS:
Since Cronbach's alpha is one of the standard ways of expressing a test’s reliability (Foster,
1998); and its coefficient is commonly used to describe the reliability factors of multi-point
formatted questionnaires or scales; the reliability of our experimental measures were assessed by
calculating Cronbach's alpha over the items of the three instruments across all the participants in
the current study which were found .73 for Adapted Inventory for Social English Language
Learning Strategies,.82 for NEO-FFI, and .80 for TOEFL. The reliability coefficient indicated
the degree to which the results on a scale can be considered internally consistent, or reliable (De
Vellis, 2003; Ghiasvand, 2008; Moemeni, 2007; Nunnally & Bernstein, 1994). Such finding of
reliabilities for the three instruments confirms the finding of reliabilities in the pilot study.

DATA COLLECTION PROCEDURES IN THE STUDY:
The data for the study described in this study was collected between September 2010 and
November 2010 in Iran.
Stage One
At this stage, the participants were asked to answer TOEFL test. Approximately 80 minutes
were taken to answer the test. Such duration of time was as the duration of time was calculated in
the pilot study (The first week).
Stage Two
At the second stage, the respondents were asked to fill the Adapted Inventory for Social English
Language Learning Strategies. The respondents were asked to respond to the questions within 5-
10 minutes. The time that assigned for participants was determined according to the results
obtained from the pilot study. Along Adapted Inventory for Social English Language Learning
Strategies, Background Questionnaire was administrated (The second week).



Stage Three
At this Stage, NEO-FFI was administrated. The time that assigned for the participants in order
to complete NEO-FFI was determined according to the results obtained from the pilot study. 10 –
15 minutes was enough to complete NEO-FFI (The third week).
DATA ANALYSIS:
After data collection, the data was entered onto databases (Excel and SPSS) to enable data
analysis to be carried out.
The First procedure of data analysis includes Pearson Correlation that used to identify the
strength and direction of the relationship between variables. In the current study, the
classification that was suggested by Cohen, J. (1988) was chosen as a criterion to interpret and
discuss about the strength of the correlation. It is as shown in Table 1: Table1: The
classification was suggested by Cohen, J (1988)

Level of Strength Amount of the Strength

Low r = .10 to .29
Medium r = .30 to .49
Strong r = .50 to 1

The second procedure of data analysis includes Analysis of Variance (ANOVA) that is an
analytic tool.
The third procedure of data analysis includes Multiple Regression Analysis.

RESULTS, DISCUSSION, AND CONCLUSION:
In the entire sample, the strategies in the Social category were the categorized as Medium
frequently used strategies, with a mean of 3.1 (SD = .79) (based on the Oxford’ key, 1990).
The means were calculated in order to determine the mean of the each of five traits of
personality among the total group of the respondents (N=213) (Table 2).



Table 2: Means and Standard Deviations (SD) of the five traits of
personality in the current study

Personality Trait N Mean SD
Neuroticism 213 23.0 8.3
Extraversion 213 27.4 5.5
Openness to Experiences 213 27.9 4.7
Agreeableness 213 32.4 5.4
Conscientiousness 213 34.7 6.3

Table 2 showed that the mean of the Conscientiousness trait (Mean = 34.7, SD = 6.3) was
more than each of the means of the other four traits, and the mean of the Neuroticism trait (Mean
= 23.0, SD = 8.3) was less than each of the means of the other four traits.
The Pearson Correlation was performed to examine whether there is relationship between the
overall Social strategy use strategies and the five traits of personality (Table 3).

Table 3: The summary of correlations among the overall Social strategy use and the five traits of
personality
Openne-
Extrave- ss to Agreeabl- Conscientio- Neurotic-
rsion Experie- eness usness ism
nces
Social Strategies Pearson .168* .212** .127 .256** -.223**
Correlation
Sig. (2-tailed) .014 .002 .064 .000 .001
N 213 213 213 213 213
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).

According to Table 3, the students’ overall Social strategy use was significant positively
correlated with the Openness to Experiences trait, and the Conscientiousness trait at the p<.01
level (2-tailed), and the Extraversion trait at the p<.05 level (2-tailed). The level of correlations
was found low for the Openness to Experiences trait, for the Conscientiousness trait, and for the
Extraversion trait. For the Neuroticism trait, the students’ overall Social strategy use was
significant negatively correlated with it at the p<.01 level (2-tailed). The level of correlation was
found low. For the Agreeableness trait, the correlation was non-significant (P>.05). In Table 3,
there were found both types of positive and negative correlations, but in both types of
correlation, the level of correlation was found low. Moreover, except the case of the


Agreeableness trait, all types of correlations were significant at the p<.01 or p<.05 levels (2-
tailed).

Table 3 indicated that based on increasing of the Extraversion trait level of the students, higher
average of Social Strategies would be used, and based on decreasing of the Extraversion trait
level, lower average of Social Strategies would be used. In such way, Table 3 showed that there
was a meaningful significant positive relationship between the overall Social strategy use and the
Extraversion trait (r = .168, p<.05). The positive relationship implies that the more extraverted
students use Social Strategies more.
Table 3 indicated that based on increasing of the Openness to Experiences trait level of the
students, higher average of Social Strategies would be used, and based on decreasing of the
Openness to Experiences trait level, lower average of Social Strategies would be used. In such
way, Table 3 showed that there was a meaningful significant positive relationship between the
overall Social strategy use and the Openness to Experiences trait (r = .212, p<.01). The positive
relationship implies that the students with higher level of Openness to Experiences trait use
Social Strategies more.
According to Table 3, the students’ overall Social strategy use was not significant correlated
with the Agreeableness trait (p>.05). In such way, Table 3 indicated that there was not a
meaningful significant relationship between the overall Social strategy use and the
Agreeableness trait.

Table 3 indicated that based on increasing of the Conscientiousness trait level of the students,
higher average of Social Strategies would be used, and based on decreasing of the
Conscientiousness trait level, lower average of Social Strategies would be used. In such way,
Table 3 showed that there was a meaningful significant positive relationship between the overall
Social strategy use and the Conscientiousness trait (r = .256, p<.01). The positive relationship
implies that the more Conscious students use Social Strategies more.
Table indicated that based on increasing of the Neuroticism trait level of the students, lower
average of Social Strategies would be used. In this way, Table 3 showed that there was a
meaningful significant negative relationship between the overall Social strategy use and the
Neuroticism trait (r = -.223, p<.01). The negative relationship implies that the more Neurotic
students use Social Strategies less.
The Multiple Regression Analysis, for all the five traits of personality (as independent variables)
and the overall use of Social Strategies (as a dependent variable) were analyzed through the
stepwise method. Out of the five traits of personality, only two variables entered the equation
(Table 4).



Table 4: The model summary of the equation
Model Variables Entered Adjusted R Std. Error of the
R R Square Square Estimate
a
1 Conscientiousness .256 .066 .061 .76566
2 Openness to .313b .098 .089 .75422
Experiences
Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-
F-to-remove >= .100).
Dependent Variable: Social Strategies
a. Predictors: (Constant), Conscientiousness
b. Predictors: (Constant), Conscientiousness, Openness to
Experiences
According to Table 4, regression analysis has run up to two steps. In the first step, the
Conscientiousness trait entered the equation that the Adjusted R-Square became .061. In the
second step, when the Openness to Experiences trait entered the equation, the Adjusted R-Square
increased up to.089. In other words, based on the Adjusted R-Square, the emerged model for the
two independent variables with the Adjusted R-Square of .089, accounted for explaining about
8.9% of the variance of the students’ overall Social strategy use.
Table 5: The results of regressional ANOVAc of the equation

Model Sum of Squares df Mean Square F Sig.
1 Regression 8.691 1 8.691 14.825 .000a
Residual 123.697 211 .586
Total 132.388 212
2 Regression 12.929 2 6.465 11.364 .000b
Residual 119.459 210 .569
Total 132.388 212
a. Predictors: (Constant), Conscientiousness
b. Predictors: (Constant), Conscientiousness, Openness to Experiences
c. Dependent Variable: Social Strategies

Further, Table 5 (regressional ANOVA) showed that the effect was significant, and all the
models had high F values (F = 14.825, F = 11.364, P<.01). Therefore, it could be concluded that
about 8.9% of changes in the students’ overall Social strategy use was accounted for by the
Conscientiousness and Openness to Experiences traits.
As hinted, Table 5 indicates that the effect of the Conscientiousness and Openness to
Experiences traits was significant at the p<.01 level. Remaining the three traits of personality did
not enter the regression equation because of level of their errors were greater than .05, and they
had very weak effect in the prediction of the overall Social strategy use. In such way, rest of the
contribution for the overall Social strategy use was unaccounted for.



Table 6: The unsatnderdised coefficientsa, t tests and significances for different models predicted
of the equation
Unstandardized Standardized
Model Coefficients Coefficients t Sig.
B Std. Error Beta
1 (Constant) 1.951 .296 6.599 .000
Conscientiousness .387 .101 .256 3.850 .000
2 (Constant) 1.217 .396 3.070 .002
Conscientiousness .350 .100 .231 3.498 .001
Openness to .362 .133 .181 2.730 .007
Experiences
a. Dependent Variable: Social Strategies

According to Table 6, although the amount of B for the Openness to Experiences was greater
than the amount of B for the Conscientiousness trait, but the Conscientiousness trait has greater
effect on change of the overall social strategy use, because of the obtained Beta for the Openness
to Experiences trait showed that for each of one unit of value of change in the Standard
Deviation of the Openness to Experiences trait, the amount of change .181 occurred in the
Standard Deviation of the overall Social strategy use; however, the obtained Beta for the
Conscientiousness trait showed that for each of one unit of value of change in its Standard
Deviation, the amount of change .231 occurred in the Standard Deviation of the overall Social
strategy use. From the above table, it was further evident that for all the predicted models and
constants, the t values ranged from 2.730 to 6.599, which all were found to be significant, and
significance levels ranged from .007 to .000 level .
Table 7 The excluded variablesc of the equation
Collinearity
Beta Partial Statistics
Model t Sig.
In Correlation
Tolerance
1 Extraversion .098a 1.403 .162 .096 .905
a
Openness to Experiences .181 2.730 .007 .185 .981
Agreeableness .066a .952 .342 .066 .934
a
Neuroticism -.154 -2.207 .028 -.151 .888
b
2 Extraversion .074 1.061 .290 .073 .888
b
Agreeableness .051 .752 .453 .052 .928
b
Neuroticism -.134 -1.919 .056 -.132 .876
a. Predictors in the Model: (Constant), Conscientiousness
b. Predictors in the Model: (Constant), Conscientiousness, Openness to Experiences
c. Dependent Variable: Social Strategies



Table 7 showed the excluded variables in this equation. The excluded variables in the first step
were Extraversion, Openness to Experiences, Agreeableness, and Neuroticism. In the second
step, the excluded variables were Extraversion, Agreeableness, and Neuroticism.
In summary, one can conclude that the traits like the Conscientiousness trait, and the Openness
to Experiences trait best predicted the overall use of Social Strategies of the students.

LIMITATIONS OF THE STUDY:
Generally speaking, there are some difficulties inherent in endeavor to conduct any
research work on the learners of second/foreign language. Similarly, the present study due to
using Ex Post facto type of research has certain limitations that must be taken in mind which
interpretation of the results. Moreover, since all the education quasi-research deals with living
human beings occur out of laboratory conditions have limitations (Gall, Gall & Borg, 2003).
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